Helen S. Mayberg

Feb 5, 2025 | nature.com | Boadie W Dunlop |Charles Nemeroff |Helen S. Mayberg |W. Edward Craighead |Victoria Aranda

Treatments for major depressive disorder (MDD) include antidepressant medications and evidence-based psychotherapies, which are approximately equally efficacious. Individual response to treatment, however, is variable, implying individual differences that could allow for prospective differential prediction of treatment response and personalized treatment recommendation. We used machine learning to develop predictor variables that combined demographic and clinical items from a randomized clinical trial. The variables predicted a meaningful proportion of variance in end-of-treatment depression severity for cognitive behavioral therapy (39.7%), escitalopram (32.1%), and duloxetine (67.7%), leading to a high accuracy in predicting remission (71%). Further, we used these variables to simulate treatment recommendation and found that patients who received their recommended treatment had significantly improved depression severity and remission likelihood. Finally, the prediction algorithms and treatment recommendation tool were externally validated in an independent sample. These results represent a highly promising, easily implemented, potential advance for personalized medicine in MDD treatment.

Jul 25, 2024 | nature.com | Mathilde Antoniades |Stephen R. Arnott |Ki Sueng Choi |Benicio N. Frey |Melanie Ganz |Beata Godlewska | +18 more

Correction to: Nature Mental Health https://doi.org/10.1038/s44220-023-00187-w, published online 12 January 2024. In the version of the article initially published, the first affiliation of Melanie Ganz was incorrect and has now been amended to Neurobiology Research Unit, University Hospital Rigshospitalet, Copenhagen, Denmark in the HTML and PDF versions of the article.

Jun 27, 2024 | nature.com | Boadie W Dunlop |Helen S. Mayberg

Circuitry-based neuroimaging analyses can enhance our understanding of abnormal brain functioning in patients with major depressive disorder and other psychiatric conditions — but their utility for guiding treatment selection is less certain.

Feb 25, 2024 | nature.com | Seth R. Batten |Dan Bang |Arianna Davis |Matthew Heflin |Ignacio Saez |Terry Lohrenz | +6 more

AbstractDopamine and serotonin are hypothesized to guide social behaviours. In humans, however, we have not yet been able to study neuromodulator dynamics as social interaction unfolds. Here, we obtained subsecond estimates of dopamine and serotonin from human substantia nigra pars reticulata during the ultimatum game. Participants, who were patients with Parkinson’s disease undergoing awake brain surgery, had to accept or reject monetary offers of varying fairness from human and computer players.

Feb 10, 2024 | biologicalpsychiatryjournal.com | Martijn Figee |Ki Sueng Choi |Andrew Smith |Helen S. Mayberg

Deep brain stimulation (DBS) in the anterior limb of the internal capsule (ALIC) is an effective treatment for obsessive-compulsive disorder (OCD). However, without a clear anatomical stimulation target within the complex ALIC region, clinical benefits are variable and require long trial-and-error periods of parameter optimization. To facilitate ALIC DBS scalability and clinical implementation, we report a method for precision ALIC DBS targeting using patient-specific tractography.